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Energy Minimization

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Computer Vision

Synonyms

Convex optimization; Convex minimization; Discrete optimization

Related Concepts

Definition

Energy minimization is a subtopic of optimization, where we minimize some energy/cost function by suitable algorithms. The type of energy is twofold: continuous and discrete.

Background

In computer vision problems, we often encounter situations of minimizing energy functions (or cost functions) that are designed to estimate, reconstruct, or process something. There are two major categories of energy minimization. One is that the target can be represented as a vector in the N-dimensional Euclidean space, i.e., the case of continuous energy. For example, if the target is a gray scale image and if each pixel value is handled as a real value, then the image can be treated as an N-dimensional vector, where Nis the number of the pixels. The other is that the target takes a discrete value, i.e., the case of discrete energy. A typical example is image segmentation...

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Author information

Authors and Affiliations

  1. Tokyo Institute of Technology, Tokyo, Japan

    Shunsuke Ono

  2. Preferred Networks, Inc., Tokyo, Japan

    Masaki Saito

Authors
  1. Shunsuke Ono
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  2. Masaki Saito
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Corresponding author

Correspondence to Shunsuke Ono .

Section Editor information

  1. Department of Computer Science and Engineering, Waseda University, Tokyo, Japan

    Hiroshi Ishikawa

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Ono, S., Saito, M. (2020). Energy Minimization. In: Computer Vision. Springer, Cham. https://doi.org/10.1007/978-3-030-03243-2_833-1

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  • DOI: https://doi.org/10.1007/978-3-030-03243-2_833-1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-03243-2

  • Online ISBN: 978-3-030-03243-2

  • eBook Packages: Springer Reference Computer SciencesReference Module Computer Science and Engineering

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